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Record W2050460033 · doi:10.1111/pbi.12308

Micro<scp>RNA</scp>156 as a promising tool for alfalfa improvement

2014· article· en· W2050460033 on OpenAlex
Banyar Aung, Margaret Y. Gruber, Lisa Amyot, Khaled W. Omari, Annick Bertrand, Abdelali Hannoufa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePlant Biotechnology Journal · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsAgriculture and Agri-Food CanadaWestern University
FundersAgriculture and Agri-Food Canada
KeywordsBiologyMedicago sativaShootTrichomeGeneCelluloseTransgeneGenetically modified cropsBotanyStarchChromosomal translocationBiochemistry

Abstract

fetched live from OpenAlex

A precursor of miR156 (MsmiR156d) was cloned and overexpressed in alfalfa (Medicago sativa L.) as a means to enhance alfalfa biomass yield. Of the five predicted SPL genes encoded by the alfalfa genome, three (SPL6, SPL12 and SPL13) contain miR156 cleavage sites and their expression was down-regulated in transgenic alfalfa plants overexpressing miR156. These transgenic plants had reduced internode length and stem thickness, enhanced shoot branching, increased trichome density, a delay in flowering time and elevated biomass production. Minor effects on sugar, starch, lignin and cellulose contents were also observed. Moreover, transgenic alfalfa plants had increased root length, while nodulation was maintained. The multitude of traits affected by miR156 may be due to the network of genes regulated by the three target SPLs. Our results show that the miR156/SPL system has strong potential as a tool to substantially improve quality and yield traits in alfalfa.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.226
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it